Scheduling Strategies for Master-Slave Tasking on Heterogeneous Processor Platforms
IEEE Transactions on Parallel and Distributed Systems
Application-Specific Scheduling for the Organic Grid
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
A Distributed Procedure for Bandwidth-Centric Scheduling of Independent-Task Applications
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Scheduling Independent Tasks Sharing Large Data Distributed with BitTorrent
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
Liana: a decentralized load-dependent scheduler for performance-cost optimization of grid service
The Journal of Supercomputing
Overlay network management for scheduling tasks on the grid
ICDCIT'07 Proceedings of the 4th international conference on Distributed computing and internet technology
Centralized versus distributed schedulers for multiple bag-of-task applications
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Master-slave tasking on asymmetric networks
Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing
A-FAST: autonomous flow approach to scheduling tasks
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
The peering problem in tree-based master/worker overlays
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
Achieving self-managed deployment in a distributed environment
Journal of Computational Methods in Sciences and Engineering
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In this paper we investigate protocols for scheduling applications that consist of large numbers of identical, independent tasks on large-scale computing platforms. By imposing a tree structure on an overlay network of computing nodes, our previous work showed that it is possible to compute the schedule which leads to the optimal steady-state task completion rate. However, implementing this optimal schedule in practice, without prohibitive global coordination of all the computing nodes or unlimited buffers, remained an open question. To address this question, in this paper we develop autonomous scheduling protocols, i.e. distributed scheduling algorithms by which each node makes scheduling decisions based solely on locally available information. Our protocols have two variants: with non-interruptible and with interruptible communications. Further, we evaluate both protocols using simulations on randomly generated trees. We show that the non-interruptible communication version may need a prohibitive number of buffers at each node. However, our autonomous protocol withinterruptible communication and only 3 buffers per node reaches the optimal steady-state performance in over 99.5% of our simulations. The autonomous scheduling approach is inherently scalable and adaptable, and thus ideally suited to currently emerging computing platforms. In particular this work has direct impact on the deployment of large applications on Grid, and peer-to-peer computing platforms.